scholarly journals Content characteristics based robust watermarking for relational database: a new approach to database security

2018 ◽  
Vol 7 (1.9) ◽  
pp. 234
Author(s):  
Manoj Kumar ◽  
O. P. Verma
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Image Watermarking ◽  
Real Life ◽  
Database Security ◽  
Vital Role ◽  
Digital Data ◽  
Secret Key ◽  
Areas Of Interest ◽  
Audio Video

Digital data such as text, relational database, audio, video and software are intellectual property of creators/ writers/owners. The database services have become easily available and economical since the booming of internet. However, their outsourcing through the internet accompanies multiple threats like copying, modifying as well as unauthorized distribution. Relational Database has a wide-spread use in many real-life applications, hence, it is essential to maintain integrity and provide copyright protection. To counter the threats, watermarking techniques have been playing a vital role since the last decade. As a security measure, Relational Database Watermarking is becoming more popular and strengthened day-by-day. This is also one of the upcoming areas of interest among researchers of the Database Security. A technique earlier used for Image Watermarking is applied to watermark Relational Databases. In Image Watermarking technique, a pixel or a pair of pixels must satisfy certain characteristics. Usually, database watermarking techniques concentrate on hiding a watermark in database. Extraction and matching of hidden watermark with original watermark confirms ownership of database. This paper demonstrates the use of image watermarking technique for relational databases. Here we align some properties of attributes of database by changing some bit(s) in attribute value. Using secret key, we have ensured that values of two attributes of a tuples satisfy some bit-similarity property and to do so, we slightly alter values of attributes. Detection of such characteristic in a database using secret key can be done easily to verify the presence of a watermark.

scholarly journals Content Characteristics Based Robust Watermarking for Relational Database: A New Approach to Database Security

2018 ◽  
Vol 7 (1.9) ◽  
pp. 302
Author(s):  
Manoj Kumar ◽  
O P. Verma
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Image Watermarking ◽  
Real Life ◽  
Database Security ◽  
Vital Role ◽  
Digital Data ◽  
Secret Key ◽  
Areas Of Interest ◽  
Audio Video

Digital data such as text, relational database, audio, video and software are intellectual property of creators/ writers/owners. The database services have become easily available and economical since the booming of internet. However, their outsourcing through the internet accompanies multiple threats like copying, modifying as well as unauthorized distribution. Relational Database has a wide-spread use in many real-life applications, hence, it is essential to maintain integrity and provide copyright protection. To counter the threats, watermarking techniques have been playing a vital role since the last decade. As a security measure, Relational Database Watermarking is becoming more popular and strengthened day-by-day. This is also one of the upcoming areas of interest among researchers of the Database Security. A technique earlier used for Image Watermarking is applied to watermark Relational Databases. In Image Watermarking technique, a pixel or a pair of pixels must satisfy certain characteristics. Usually, database watermarking techniques concentrate on hiding a watermark in database. Extraction and matching of hidden watermark with original watermark confirms ownership of database. This paper demonstrates the use of image watermarking technique for relational databases. Here we align some properties of attributes of database by changing some bit(s) in attribute value. Using secret key, we have ensured that values of two attributes of a tuples satisfy some bit-similarity property and to do so, we slightly alter values of attributes. Detection of such characteristic in a database using secret key can be done easily to verify the presence of a watermark.  

scholarly journals Image Security using Digital Image Watermarking and Visual Cryptography Techniques

2020 ◽  
Vol 9 (4) ◽  
pp. 2386-2391
Keyword(s):  
Digital Media ◽  
Digital Image ◽  
Image Watermarking ◽  
Visual Cryptography ◽  
Digital Data ◽  
Digital Image Watermarking ◽  
Digital Information ◽  
Secret Key ◽  
Public Networks ◽  
Real Time Application

In today’s world, the enhancement in internet technologies, digital data are mostly used to share the information in public networks. There are many traditional security techniques used to provide security to the digital information. But the existing methods don’t provide much of the security to digital media like image, video, audio, etc. The digital watermarking is employed in the protection of digital information. This paper gives a review on digital image watermarking based on the visual cryptography to reach secure protection for the images. The secret information can be inserted in the original images. The secret key is generated from the watermark image with the help of visual cryptography to claim the ownership of images. Various types of Visual Cryptography and Digital Image Watermarking techniques are explained in real time application.

scholarly journals GRAYSCALE IMAGE WATERMARK DETECTION

2012 ◽  
Vol 3 (1) ◽  
pp. 100-105
Author(s):  
Randeep Kaur ◽  
Kamaljit Kaur Dhillon
Keyword(s):  
Image Watermarking ◽  
Research Work ◽  
Digital Data ◽  
Digital Image Watermarking ◽  
Still Images ◽  
Dct Domain ◽  
Textual Data ◽  
Digital Watermarks ◽  
Comparative Results ◽  
Audio Video

A Digital watermarking is a technique that provides a solution to the longstanding problems faced with copyrighting digital data. Digital watermarks are pieces of information added to digital data (audio, video, or still images) that can be detected or extracted later to make an assertion about the data. This information can be textual data about the author, its copyright, etc; or it can be an image itself. Watermarking Based on DCT Coefficient Modulation technique embeds the watermark in the DCT domain to increase the robustness of the watermarking scheme.DCT based watermarking is an example of frequency domain watermarking. The objective of this research work is to implement DCT based watermarking technique on gray scale image. The study focuses on evaluating the robustness of watermarked image after having three different attacks on watermarked image and extraction of watermark from that particular image. To compare the DCT based watermarking with LSB based watermarking and to validate the proposed work & the comparative results of watermarking using DCT and LSB are also presented. This paper recommends DCT based technique for achieving robustness in digital image watermarking.

scholarly journals A Blind Reversible Robust Watermarking Scheme for Relational Databases

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chin-Chen Chang ◽  
Thai-Son Nguyen ◽  
Chia-Chen Lin
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Digital Data ◽  
Data Embedding ◽  
Robust Watermarking ◽  
Extensive Analysis ◽  
Proof Of Ownership ◽  
Reversible Data Embedding ◽  
Adjacent Pixel ◽  
Watermarking Scheme

Protecting the ownership and controlling the copies of digital data have become very important issues in Internet-based applications. Reversible watermark technology allows the distortion-free recovery of relational databases after the embedded watermark data are detected or verified. In this paper, we propose a new, blind, reversible, robust watermarking scheme that can be used to provide proof of ownership for the owner of a relational database. In the proposed scheme, a reversible data-embedding algorithm, which is referred to as “histogram shifting of adjacent pixel difference” (APD), is used to obtain reversibility. The proposed scheme can detect successfully 100% of the embedded watermark data, even if as much as 80% of the watermarked relational database is altered. Our extensive analysis and experimental results show that the proposed scheme is robust against a variety of data attacks, for example, alteration attacks, deletion attacks, mix-match attacks, and sorting attacks.

scholarly journals Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3953
Author(s):  
Han Pu ◽  
Tianqiang Huang ◽  
Bin Weng ◽  
Feng Ye ◽  
Chenbin Zhao
Keyword(s):  
Detection Method ◽  
Real Life ◽  
Vital Role ◽  
Video Forensics ◽  
Flow Algorithm ◽  
Benchmark Datasets ◽  
Media Reports ◽  
Intensity Normalization ◽  
Inter Frame ◽  
Stable Feature

Digital video forensics plays a vital role in judicial forensics, media reports, e-commerce, finance, and public security. Although many methods have been developed, there is currently no efficient solution to real-life videos with illumination noises and jitter noises. To solve this issue, we propose a detection method that adapts to brightness and jitter for video inter-frame forgery. For videos with severe brightness changes, we relax the brightness constancy constraint and adopt intensity normalization to propose a new optical flow algorithm. For videos with large jitter noises, we introduce motion entropy to detect the jitter and extract the stable feature of texture changes fraction for double-checking. Experimental results show that, compared with previous algorithms, the proposed method is more accurate and robust for videos with significant brightness variance or videos with heavy jitter on public benchmark datasets.

Using digital data collection tools to improve overall cost-efficiency and provide timely analysis for decision making during invasive species eradication campaigns

2014 ◽  
Vol 41 (6) ◽  
pp. 499 ◽  
Author(s):  
David J. Will ◽  
Karl J. Campbell ◽  
Nick D. Holmes
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Cost Efficiency ◽  
Relational Databases ◽  
Cost Effective ◽  
Digital Data ◽  
Capital Costs ◽  
Project Costs ◽  
Time Required ◽  
Data Collection Effort

Context Worldwide, invasive vertebrate eradication campaigns are increasing in scale and complexity, requiring improved decision making tools to achieve and validate success. For managers of these campaigns, gaining access to timely summaries of field data can increase cost-efficiency and the likelihood of success, particularly for successive control-event style eradications. Conventional data collection techniques can be time intensive and burdensome to process. Recent advances in digital tools can reduce the time required to collect and process field information. Through timely analysis, efficiently collected data can inform decision making for managers both tactically, such as where to prioritise search effort, and strategically, such as when to transition from the eradication phase to confirmation monitoring. Aims We highlighted the advantages of using digital data collection tools, particularly the potential for reduced project costs through a decrease in effort and the ability to increase eradication efficiency by enabling explicit data-informed decision making. Methods We designed and utilised digital data collection tools, relational databases and a suite of analyses during two different eradication campaigns to inform management decisions: a feral cat eradication utilising trapping, and a rodent eradication using bait stations. Key results By using digital data collection during a 2-year long cat eradication, we experienced an 89% reduction in data collection effort and an estimated USD42 845 reduction in total costs compared with conventional paper methods. During a 2-month rodent bait station eradication, we experienced an 84% reduction in data collection effort and an estimated USD4525 increase in total costs. Conclusions Despite high initial capital costs, digital data collection systems provide increasing economics as the duration and scale of the campaign increases. Initial investments can be recouped by reusing equipment and software on subsequent projects, making digital data collection more cost-effective for programs contemplating multiple eradications. Implications With proper pre-planning, digital data collection systems can be integrated with quantitative models that generate timely forecasts of the effort required to remove all target animals and estimate the probability that eradication has been achieved to a desired level of confidence, thus improving decision making power and further reducing total project costs.

scholarly journals Enhanced Image Security using New Sea Lion Optimization Algorithm

2020 ◽  
Vol 9 (7) ◽  
pp. 22-25
Keyword(s):  
Optimization Algorithm ◽  
Electronic Communication ◽  
Digital Data ◽  
Sea Lion ◽  
Image Security ◽  
Encryption And Decryption ◽  
Recent Developments ◽  
Encryption Algorithms ◽  
Lion Optimization Algorithm ◽  
Audio Video

Protection of digital data is the utmost requirement of the day. Everything in the world is being upgraded to electronic communication and which requires protection against data fraud. Data is nowadays not only text but image, audio video individually and sometimes together as multimedia files. Encryption algorithms protect data against attacks and hackers. This paper proposes a new Sealion Optimization algorithm for enhanced image security, analyses several recent developments in encryption and decryption algorithms and summarizes different approaches, their benefits and limitations.

Potential Security Issues in a Peer-to-Peer Network from a Database Perspective

2011 ◽  
pp. 131-144
Author(s):  
Sridhar Asvathanarayanan
Keyword(s):  
Denial Of Service ◽  
Database Security ◽  
Vital Role ◽  
Peer To Peer ◽  
Peer Networks ◽  
Distributed Denial Of Service ◽  
Security Issues ◽  
Peer Network ◽  
Peer To Peer Networks ◽  
Peer To Peer Network

Computing strategies have constantly undergone changes, from being completely centralized to client-servers and now to peer-to-peer networks. Databases on peer-to-peer networks offer significant advantages in terms of providing autonomy to data owners, to store and manage the data that they work with and, at the same time, allow access to others. The issue of database security becomes a lot more complicated and the vulnerabilities associated with databases are far more pronounced when considering databases on a peer-to-peer network. Issues associated with database security in a peer-to-peer environment could be due to file sharing, distributed denial of service, and so forth, and trust plays a vital role in ensuring security. The components of trust in terms of authentication, authorization, and encryption offer methods to ensure security.

A Framework on Data Mining on Uncertain Data with Related Research Issues in Service Industry

Data Mining ◽  
2013 ◽  
pp. 515-529
Author(s):  
Edward Hung
Keyword(s):  
Data Mining ◽  
Relational Databases ◽  
Service Industry ◽  
Uncertain Data ◽  
Research Work ◽  
Real Life ◽  
Mean Value ◽  
Customer Relationship ◽  
Statistical Classifiers ◽  
Targeted Marketing

There has been a large amount of research work done on mining on relational databases that store data in exact values. However, in many real-life applications such as those commonly used in service industry, the raw data are usually uncertain when they are collected or produced. Sources of uncertain data include readings from sensors (such as RFID tagged in products in retail stores), classification results (e.g., identities of products or customers) of image processing using statistical classifiers, results from predictive programs used for stock market or targeted marketing as well as predictive churn model in customer relationship management. However, since traditional databases only store exact values, uncertain data are usually transformed into exact data by, for example, taking the mean value (for quantitative attributes) or by taking the value with the highest frequency or possibility. The shortcomings are obvious: (1) by approximating the uncertain source data values, the results from the mining tasks will also be approximate and may be wrong; (2) useful probabilistic information may be omitted from the results. Research on probabilistic databases began in 1980s. While there has been a great deal of work on supporting uncertainty in databases, there is increasing work on mining on such uncertain data. By classifying uncertain data into different categories, a framework is proposed to develop different probabilistic data mining techniques that can be applied directly on uncertain data in order to produce results that preserve the accuracy. In this chapter, we introduce the framework with a scheme to categorize uncertain data with different properties. We also propose a variety of definitions and approaches for different mining tasks on uncertain data with different properties. The advances in data mining application in this aspect are expected to improve the quality of services provided in various service industries.

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